IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v31y2008i4p397-408.html
   My bibliography  Save this article

Two Dimensional Aggregation Procedure: An Alternative to the Matrix Algebraic Algorithm

Author

Listed:
  • Rodolphe Buda

Abstract

No abstract is available for this item.

Suggested Citation

  • Rodolphe Buda, 2008. "Two Dimensional Aggregation Procedure: An Alternative to the Matrix Algebraic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 31(4), pages 397-408, May.
    • Handle: RePEc:kap:compec:v:31:y:2008:i:4:p:397-408
    DOI: 10.1007/s10614-008-9123-9
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10614-008-9123-9
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10614-008-9123-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Matteo Richiardi & Roberto Leombruni & Nicole J. Saam & Michele Sonnessa, 2006. "A Common Protocol for Agent-Based Social Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(1), pages 1-15.
    2. Michael Binder, 2001. "Cross-Sectional Aggregation of Nonlinear Dynamic Models and Aggregate Consumption Dynamics," Computing in Economics and Finance 2001 37, Society for Computational Economics.
    3. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    4. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, University Library of Munich, Germany, revised 15 Aug 2002.
    5. Eric R Young, 2005. "Approximate Aggregation," Computing in Economics and Finance 2005 141, Society for Computational Economics.
    6. Buda, Rodolphe, 2001. "Les algorithmes de la modélisation : une analyse critique pour la modélisation économique," MPRA Paper 3926, University Library of Munich, Germany, revised Jul 2004.
    7. Stephan von Cramon-Taubadel & Jens-Peter Loy & Jochen Meyer, 2006. "The impact of cross-sectional data aggregation on the measurement of vertical price transmission: An experiment with German food prices," Agribusiness, John Wiley & Sons, Ltd., vol. 22(4), pages 505-522.
    8. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    9. Gibbons, Joel C. & Wolsky, Alan M. & Tolley, George, 1982. "Approximate aggregation and error in input-output models," Resources and Energy, Elsevier, vol. 4(3), pages 203-230, September.
    10. Buda, Rodolphe, 2005. "Numerical Analysis in Econom(etr)ic Softwares: the Data-Memory Shortage Management," MPRA Paper 9145, University Library of Munich, Germany, revised 2007.
    11. Michael L. Lahr & Benjamin H. Stevens, 2002. "A Study of the Role of Regionalization in the Generation of Aggregation Error in Regional Input –Output Models," Journal of Regional Science, Wiley Blackwell, vol. 42(3), pages 477-507, August.
    12. van Garderen, Kees Jan & Lee, Kevin & Pesaran, M. Hashem, 2000. "Cross-sectional aggregation of non-linear models," Journal of Econometrics, Elsevier, vol. 95(2), pages 285-331, April.
    13. Tzu-Tsung Wong, 2007. "Perfect aggregation of Bayesian analysis on compositional data," Statistical Papers, Springer, vol. 48(2), pages 265-282, April.
    14. Buchholz, Peter, 1999. "An adaptive aggregation/disaggregation algorithm for hierarchical Markovian models," European Journal of Operational Research, Elsevier, vol. 116(3), pages 545-564, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rodolphe Buda, 2013. "SIMUL 3.2: An Econometric Tool for Multidimensional Modelling," Computational Economics, Springer;Society for Computational Economics, vol. 41(4), pages 517-524, April.
    2. Buda, Rodolphe, 2008. "Contrôle des systèmes de modélisation : un exemple de codage et de traçabilité des données [Modelling System Checking : An Example of Data Encoding and Traceability]," MPRA Paper 47209, University Library of Munich, Germany.
    3. Rodolphe Buda, 2015. "Data Checking and Econometric Software Development: A Technique of Traceability by Fictive Data Encoding," Computational Economics, Springer;Society for Computational Economics, vol. 46(2), pages 325-357, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. G. Fagiolo & C. Birchenhall & P. Windrum, 2007. "Empirical Validation in Agent-based Models: Introduction to the Special Issue," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 189-194, October.
    2. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
    3. Paul L. Borrill & Leigh Tesfatsion, 2011. "Agent-based Modeling: The Right Mathematics for the Social Sciences?," Chapters, in: John B. Davis & D. Wade Hands (ed.), The Elgar Companion to Recent Economic Methodology, chapter 11, Edward Elgar Publishing.
    4. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    5. Frijns, Bart & Lehnert, Thorsten & Zwinkels, Remco C.J., 2010. "Behavioral heterogeneity in the option market," Journal of Economic Dynamics and Control, Elsevier, vol. 34(11), pages 2273-2287, November.
    6. Flaminio Squazzoni, 2010. "The impact of agent-based models in the social sciences after 15 years of incursions," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 197-234.
    7. Domenico Gatti & Edoardo Gaffeo & Mauro Gallegati, 2010. "Complex agent-based macroeconomics: a manifesto for a new paradigm," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 5(2), pages 111-135, December.
    8. Francesco Lamperti, 2015. "An Information Theoretic Criterion for Empirical Validation of Time Series Models," LEM Papers Series 2015/02, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    9. Li, Hongyan & Sun, Junjie & Tesfatsion, Leigh, 2010. "Testing institutional arrangements via agent-based modeling: a U.S. electricity market example," ISU General Staff Papers 201002020800001088, Iowa State University, Department of Economics.
    10. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2013. "Time-varying beta: a boundedly rational equilibrium approach," Journal of Evolutionary Economics, Springer, vol. 23(3), pages 609-639, July.
    11. Paola Tubaro, 2011. "Computational Economics," Chapters, in: John B. Davis & D. Wade Hands (ed.), The Elgar Companion to Recent Economic Methodology, chapter 10, Edward Elgar Publishing.
    12. Albert Banal-Estañol & Augusto Rupérez-Micola, 2010. "Are agent-based simulations robust? The wholesale electricity trading case," Economics Working Papers 1214, Department of Economics and Business, Universitat Pompeu Fabra.
    13. Annalisa Fabretti, 2013. "On the problem of calibrating an agent based model for financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(2), pages 277-293, October.
    14. Myong-Hun Chang, 2009. "Industry dynamics with knowledge-based competition: a computational study of entry and exit patterns," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 4(1), pages 73-114, June.
    15. Junjie Sun & Leigh Tesfatsion, 2007. "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 291-327, October.
    16. Andreas Fuster & Benjamin Hebert & David Laibson, 2012. "Natural Expectations, Macroeconomic Dynamics, and Asset Pricing," NBER Macroeconomics Annual, University of Chicago Press, vol. 26(1), pages 1-48.
    17. Assenza, T. & Delli Gatti, D. & Gallegati, M., 2007. "Heterogeneity and Aggregation in a Financial Accelerator Model," CeNDEF Working Papers 07-13, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    18. Friederike Wall, 2016. "Agent-based modeling in managerial science: an illustrative survey and study," Review of Managerial Science, Springer, vol. 10(1), pages 135-193, January.
    19. Giorgio Fagiolo & Alessio Moneta & Paul Windrum, 2007. "A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies, Procedures, and Open Problems," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 195-226, October.
    20. Rodolphe Buda, 2015. "Data Checking and Econometric Software Development: A Technique of Traceability by Fictive Data Encoding," Computational Economics, Springer;Society for Computational Economics, vol. 46(2), pages 325-357, August.

    More about this item

    Keywords

    Matrix algebra; Aggregation algorithms; Modelling software; C82; C87; C88;
    All these keywords.

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

    Lists

    This item is featured on the following reading lists, Wikipedia, or ReplicationWiki pages:
    1. Matrice creuse in Wikipedia French

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:compec:v:31:y:2008:i:4:p:397-408. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.